With the advent of the Internet, social networking and blogging services have resulted in growing use of these interactive media platforms for communicating information. In particular, social media tags provide a text-driven indexing system within network communities often used for linking content to a particular meme, topic, or person. Social media tags may take various forms, for example a hashtag (e.g., #Topic) or an @-symbol (e.g., @Person).
The integration of social media in television has further changed how social interaction and communication occurs. In particular, television programs, including TV shows and advertisements, are utilizing social media tags to promote and share news and information about TV shows, brands, products, personalities (e.g., political figures, celebrities) and political campaigns. At times, social media tags are announced in the audio portion of television content or through closed captioning. Often, social media tags are embedded within the picture portion of television content.
Systems for recognizing text within images or video are known in the art. One such system is described in U.S. Pat. No. 8,320,674 to Guillou et al. However, the system of Guillou is designed for identifying and recognizing text within a single stream of video and is not configured to concurrently receive, handle, and recognize text with multiple video streams. The system also includes other disadvantages. For example, it does not track or collect metadata information pertaining to each detected text, such as the channel/station in which the text appeared, the date and time the text appeared, or the location of the text within the video frame. Such information is relevant in evaluating the coverage, reach, influence, impact and resulting sentiment that the text has on respective audiences. Further, the system does not analyze the detected text to determine whether the text is related to a social media tag, and does not perform any analysis of social media events (e.g., commentary, tweet, wall posting, messaging, etc.) generated in response to the text appearing in the video. The system also fails to address issues with efficiently handling and managing large amounts of video and conducting character recognition scans (e.g., optical character recognition) of the video, which are data-intensive and computing-intensive processes.
Therefore, it would be beneficial to provide a system and method for detecting text embedded in video and/or images and evaluating the detected text for social media tags. It is further beneficial to provide a system and method that tracks social media events created in response to the media tags appearing in video and generating analytics data concerning social media events.